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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Unsupervised Machine Learning for Lithological Mapping Using Geochemical Data in Covered Areas of Jining, China
Guopeng Wu, Guoxiong Chen, Qiuming Cheng, et al.
Natural Resources Research (2021) Vol. 30, Iss. 2, pp. 1053-1068
Closed Access | Times Cited: 25

Showing 25 citing articles:

A review of machine learning in geochemistry and cosmochemistry: Method improvements and applications
Yuyang He, You Zhou, Tao Wen, et al.
Applied Geochemistry (2022) Vol. 140, pp. 105273-105273
Open Access | Times Cited: 54
Mapping homogeneous regions for flash floods using machine learning: A case study in Jiangxi province, China
Ruojing Zhang, Yuehong Chen, Xiaoxiang Zhang, et al.
International Journal of Applied Earth Observation and Geoinformation (2022) Vol. 108, pp. 102717-102717
Open Access | Times Cited: 49
Effective delineation of rare metal-bearing granites from remote sensing data using machine learning methods: A case study from the Umm Naggat Area, Central Eastern Desert, Egypt
Mohamed Abdelkader, Yasushi Watanabe, Ali Shebl, et al.
Ore Geology Reviews (2022) Vol. 150, pp. 105184-105184
Open Access | Times Cited: 37
Research on 3D Geological Modeling Method Based on Deep Neural Networks for Drilling Data
Liang Liu, Tianbin Li, Chunchi Ma
Applied Sciences (2024) Vol. 14, Iss. 1, pp. 423-423
Open Access | Times Cited: 8
Geochemical survey data cube: A useful tool for lithological classification and geochemical anomaly identification
Ying Xu, Renguang Zuo
Geochemistry (2023) Vol. 84, Iss. 2, pp. 125959-125959
Closed Access | Times Cited: 14
Geological Mapping Using Direct Sampling and a Convolutional Neural Network Based on Geochemical Survey Data
Ziye Wang, Renguang Zuo, Fanfan Yang
Mathematical Geosciences (2022) Vol. 55, Iss. 7, pp. 1035-1058
Closed Access | Times Cited: 20
Lithological Mapping Using a Convolutional Neural Network based on Stream Sediment Geochemical Survey Data
Xue-ping Wang, Renguang Zuo, Ziye Wang
Natural Resources Research (2022) Vol. 31, Iss. 5, pp. 2397-2412
Closed Access | Times Cited: 18
Data-driven expeditious mapping and identifying granites in covered areas via deep machine learning: A case study on the implications for geodynamics and mineralization of Eastern Tianshan
Fan Xiao, Antony Tang, Huaqing Yang, et al.
Lithos (2025), pp. 107947-107947
Closed Access
Ensemble machine learning model for exploration and targeting of Pb-Zn deposits in Algeria
Selma Remidi, Abdelhak Boutaleb, Salah Eddine Tachi, et al.
Earth Science Informatics (2025) Vol. 18, Iss. 2
Closed Access
Data Mining for Cognitive e-Learning Systems: A Survey
Saniya Zahoor, Shabir Ahmad Sofi
Procedia Computer Science (2025) Vol. 259, pp. 1803-1808
Open Access
Leucogranite mapping via convolutional recurrent neural networks and geochemical survey data in the Himalayan orogen
Ziye Wang, Tong Li, Renguang Zuo
Geoscience Frontiers (2023) Vol. 15, Iss. 1, pp. 101715-101715
Open Access | Times Cited: 9
Remote sensing and geochemistry of A-type granites, North Arabian-Nubian shield: Insights into the origin and evolution of the granitic suites and processes responsible for rare metals enrichment
Saif M. Abo Khashaba, N. H. El-Shibiny, Safaa M. Hassan, et al.
Ore Geology Reviews (2024) Vol. 175, pp. 106391-106391
Open Access | Times Cited: 3
Geological mapping of basalt using stream sediment geochemical data: Case study of covered areas in Jining, Inner Mongolia, China
Yunzhao Ge, Zhenjie Zhang, Qiuming Cheng, et al.
Journal of Geochemical Exploration (2021) Vol. 232, pp. 106888-106888
Closed Access | Times Cited: 19
Bedrock mapping based on terrain weighted directed graph convolutional network using stream sediment geochemical samplings
Baoyi Zhang, Man-Yi Li, Yuke Huan, et al.
Transactions of Nonferrous Metals Society of China (2023) Vol. 33, Iss. 9, pp. 2299-2814
Open Access | Times Cited: 8
Multi-Scale Potential Field Data Integration Using Fuzzy C-Means Clustering for Automated Geological Mapping of North Singhbhum Mobile Belt, Eastern Indian Craton
K. Santosh, Rama Chandrudu Arasada, G. Srinivasa Rao
Minerals (2023) Vol. 13, Iss. 8, pp. 1014-1014
Open Access | Times Cited: 7
Multitarget Intelligent Recognition of Petrographic Thin Section Images Based on Faster RCNN
Hanyu Wang, Wei Cao, Yongzhang Zhou, et al.
Minerals (2023) Vol. 13, Iss. 7, pp. 872-872
Open Access | Times Cited: 6
Incorporation of geological constraints into geochemical anomaly identification using BME-GWR: A case study from Inner Mongolia of China
Haicheng Wang, Zhaoxian Yuan, Qiuming Cheng, et al.
Ore Geology Reviews (2021) Vol. 141, pp. 104658-104658
Open Access | Times Cited: 10
Recognizing geochemical patterns related to mineralization using a self-organizing map
Zhiyi Chen, Yihui Xiong, Bojun Yin, et al.
Applied Geochemistry (2023) Vol. 151, pp. 105621-105621
Closed Access | Times Cited: 4
3D pseudo-lithologic modeling via iterative weighted k-means++ algorithm from Tengger Desert cover area, China
Yulong Dong, Yang Liu, Wuxu Peng, et al.
Frontiers in Earth Science (2023) Vol. 11
Open Access | Times Cited: 4
Graph convolutional network for lithological classification and mapping using stream sediment geochemical data and geophysical data
Fang Hao, Yue Liu, Qingteng Zhang
Geochemistry Exploration Environment Analysis (2024) Vol. 24, Iss. 2
Closed Access | Times Cited: 1
Optimizing multi-classifier fusion for seabed sediment classification using machine learning
Michael Anokye, Xiaodong Cui, Fanlin Yang, et al.
International Journal of Digital Earth (2023) Vol. 17, Iss. 1
Open Access | Times Cited: 3
Three-Dimensional Pseudo-Lithologic Modeling Via Adaptive Feature Weighted k-Means Algorithm from Multi-Source Geophysical Datasets, Qingchengzi Pb–Zn–Ag–Au District, China
Zhiqiang Zhang, Gongwen Wang, Emmanuel John M. Carranza, et al.
Natural Resources Research (2021) Vol. 31, Iss. 4, pp. 2163-2179
Closed Access | Times Cited: 7
Machine Learning Fusion Multi-Source Data Features for Classification Prediction of Lunar Surface Geological Units
Wei Zuo, Xingguo Zeng, Xingye Gao, et al.
Remote Sensing (2022) Vol. 14, Iss. 20, pp. 5075-5075
Open Access | Times Cited: 5
Predictive lithology mapping using semisupervised learning: Practical insights using a case study from New South Wales, Australia
Michael W. Dunham, Alison Malcolm, J. Kim Welford
Geophysics (2023) Vol. 88, Iss. 3, pp. JM1-JM17
Closed Access | Times Cited: 2
Lithology Identification of UAV Oblique Photography Images Based on Semantic Segmentation Neural Network Algorithm
Siyu Luo, Senlin Yin, Juan Chen, et al.
Mathematical Geosciences (2023) Vol. 56, Iss. 5, pp. 1053-1072
Closed Access | Times Cited: 2
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